Triple

T9914901
Position Surface form Disambiguated ID Type / Status
Subject Jean Gabin E185842 entity
Predicate notableWork P4 FINISHED
Object French Cancan E548272 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: French Cancan | Statement: [Jean Gabin, notableWork, French Cancan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: French Cancan
Context triple: [Jean Gabin, notableWork, French Cancan]
  • A. French Cancan chosen
    French Cancan is a 1955 French musical film by Jean Renoir that colorfully dramatizes the origins of the cancan dance in Paris’s Montmartre.
  • B. Folies Bergère
    Folies Bergère is a historic Parisian music hall and cabaret, famed for its lavish variety shows, elaborate costumes, and role in the development of French popular entertainment.
  • C. La Goulue
    La Goulue was the stage name of Louise Weber, a famous late-19th-century French can-can dancer at the Moulin Rouge and a popular subject of Toulouse-Lautrec’s posters.
  • D. Dranse
    The Dranse is a river in the Haute-Savoie region of France that flows from the Alps into Lake Geneva near Thonon-les-Bains.
  • E. Calaisienne
    Calaisienne is the French term for a female inhabitant or native of the port city of Calais in northern France.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ca829b45f481909040f7b99a1976ed completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb53ba1ac8190ba655133b81596d7 completed April 2, 2026, 12:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20dd82edc8190b405a3969864af77 completed April 5, 2026, 7:23 a.m.
Created at: March 30, 2026, 8:41 p.m.